Find Academic Supervisors

David HarelView profile

Professor

• Computability Theory
• Logics of Programs
• Database Theory
• +7 more

Prof. David Harel is a distinguished academic at the Weizmann Institute of Science, holding the William Sussman Professorial Chair since 1980. He has served as Head of the Department of Applied Mathematics and Computer Science (1989–1995) and Dean of the Faculty of Mathematics and Computer Science (1998–2005). He currently leads the John von Neumann Minerva Center for the Development of Reactive Systems. His scholarly contributions span theoretical computer science and applied systems engineering. Education: BSc, Bar-Ilan University (1974) MSc, Tel-Aviv University (1976) PhD, Massachusetts Institute of Technology (1978) His research bridges fundamental and applied domains, including computability theory (levels of undecidability), logics of programs (dynamic logic), database theory (query languages), and automata theory . Later work focused on software and systems engineering , visual languages, biological modeling, and innovative odor communication systems. Scientific Honors: ACM Karlstrom Outstanding Educator Award (1992) Stevens Award (1996) Israel Prize (2004) ACM SIGSOFT Awards (2006, 2008) Emet Prize (2010) Fellowships: ACM, IEEE, AAAS, Academia Europaea Harel co-founded I-Logix, Inc. (1984), whose tools (Statemate, Rhapsody, Play-Engine) influenced UML behavioral modeling. He invented statecharts and co-invented live sequence charts (LSCs) and reactive animation . His expository works include the popular science books Computers Ltd. and Algorithmics .

• Database Systems
• Software Engineering
• Data Integration
• +3 more

Roger King is a seasoned researcher with over 40 years of contributions to computer science, particularly in database systems, software engineering, and data integration. His work spans heterogeneous database management, semantic modeling, and distributed systems, often collaborating with leading institutions like University of Colorado and Springer. 1987: Co-authored foundational paper on semantic database modeling in ACM Computing Surveys 1992: Developed FaceKit database interface design toolkit 1994: Pioneered DIRECT query facility for multiple databases Research Interests: King's work focuses on database integration , semantic interoperability , and self-adaptive systems . Notable projects include Sybil for database evolution, Cactis for object-oriented databases, and COIL mediator definition language. Key Trends: His 15 most recent publications (2024-1999) address challenges in smart data systems , autonomous systems performance , and microgrid control , reflecting sustained expertise in data semantics and system architecture.

• Semantic Web Services
• B2B Integration
• Workflow Management
• +3 more

Christoph Bussler is a prominent researcher with extensive contributions to Semantic Web Services B2B Integration Cloud Computing Workflow Management Enterprise Application Integration His work focuses on semantic technologies, data engineering, and optimization frameworks. Recent publications analyze Cloud storage tier optimization Graph-based cost modeling Taxonomy for cloud storage costs Serverless-container hybrid systems SQL for NoSQL databases These studies emphasize scalable solutions and semantic interoperability. He has collaborated with experts like Dumitru Roman, Radu Prodan, and Dieter Fensel on projects involving Triple Space Computing WSMX Architecture Peer-to-Peer Service Discovery Rule-Based Classification

Hongbo DuView profile

Professor

• Data Mining
• Machine Learning
• Image Processing
• +3 more

Professor Hongbo Du is a faculty member at the University of Buckingham's School of Computing within the Faculty of Computing, Law and Psychology. He holds a BSc in Computer Automation from Beijing, an MSc in Computing from the University of Essex, and an MPhil in Computing. His research focuses on Data Mining, Machine Learning, Image Processing, and Time Series Analysis with applications in medical diagnostics. Notable collaborations include work with TenD Medical AI Technologies, DeepNet Security, and the Wellcome Trust Sanger Institute. He currently leads modules like Principles of Database Systems and Applied Techniques of Data Mining and Machine Learning, and directs GPP collaboration programmes. His research emphasizes practical problem-solving using machine learning, particularly in analyzing ultrasound and biomedical images for cancer diagnosis (e.g., breast and thyroid lesions). He has supervised multiple PhD and MRes projects in medical image analysis and co-authored numerous peer-reviewed publications. His work spans from technical innovations like Clustered-CAM visualization techniques to clinical applications such as Doppler feature analysis for thyroid cancer detection. Prof Du's contributions extend to curriculum development and educational methodologies, including data mining pedagogy. His projects often involve interdisciplinary approaches, combining medical expertise with computational techniques to address healthcare challenges.

Pierre Yves SchobbensView profile

Professor

• Software Product Lines
• Software Verification
• Formal Methods
• +5 more

Pierre Yves Schobbens is a Professor of Computer Science at the Université Catholique de Louvain, specializing in software product lines verification, formal methods, and agent-oriented programming. He holds leadership roles including President of the Precise research center and the international affairs commission of the Faculty of Computer Science. His research focuses on software reliability, energy-aware systems, and real-time systems. Education: Bachelor in Philosophy (1982) Master in Applied Mathematics and Economics (1983) Master in Computer Engineering (1984) Doctorate in Computer Science (1993) Research Interests: Software Product Line Verification Model Checking Formal Methods for Real-Time Systems Energy Efficiency in Neural Architectures Agent-Oriented Programming Key Contributions: Development of featured transition systems for variability analysis Advances in mutation testing for timed systems Tools like ProVeLines for software product line verification Awards: Most influential paper award (IEEE RE 2016) Best paper (SAFECOMP 2012) 2024 VAMOS Ten-Year Most Influential Paper Award Grants & Projects: Lead on SQUAL.AI (AI-driven software quality) ERNEST (energy-efficient IoT scheduling) CFV (Center for Software Verification) He collaborates extensively with institutions like the Ecole Normale Supérieure and the University of Birmingham, and has supervised over 90 research works.

Richard ScamellView profile

Professor

• Database Management Systems
• Research Methodology
• Impact of Information Systems on Organizational Dynamics
• +3 more

Richard Scamell is a Professor and Associate Dean for Student Affairs in the Decision and Information Sciences Department at the C. T. Bauer College of Business, University of Houston. He has been at the University since 1972, contributing over five decades to academia. Scamell holds a Ph.D., MBA, and B.A. in Statistics and Operations Research from the University of Texas at Austin. His teaching focuses on Database Management Systems, Decision Support Systems, and MIS Research Methods. He has advised over 60 doctoral students, chairing 16 committees, and received multiple Excellence in Teaching awards. His research spans database systems, information systems impact on organizations, and groupware acceptance, with publications in MIS Quarterly , Management Science , and IEEE Transactions . He co-authored Data Modeling and Database Design (Cengage Learning, 2015). Scamell serves as the NCAA Faculty Athletics Representative and has held interim roles in university administration. His work emphasizes human-centered IT design and organizational dynamics. Research Interests : Database Management Systems, Human-Computer Interface, Information Systems Impact, Research Methodology. Key Contributions : Pioneering studies in groupware adoption, SQL vs. QBE usability, and long-term academic service. His research bridges technology and organizational behavior, emphasizing practical applications in education and industry.

• Artificial Intelligence
• Data Science
• Future Internet Architecture
• +2 more

Mohammad Arifuzzaman is an Assistant Professor in the Mathematics, Statistics & Computer Science Department at the University of Wisconsin-Stout. His research focuses on Artificial Intelligence, Data Science, Future Internet Architecture, Green Wireless Communication, and Sensor Networks. He holds a Ph.D. in Computer Systems & Network Engineering from Waseda University, Japan, and completed postdoctoral training at Memorial University of Newfoundland, Canada. Education: Ph.D. in Computer Systems & Network Engineering, Waseda University, Japan Postdoctoral Fellow, Memorial University of Newfoundland, Canada His scholarly work spans AI, cybersecurity, graph data mining, and sustainable networking. Recent publications emphasize deep learning for dialect recognition, sentiment analysis, and phishing detection. He has contributed to international projects like GreenICN (EU-Japan) and ITU-T standardization efforts for future networks. Scientific awards include the Best Paper Award at ITU Kaleidoscope Conference (2011). He has published over 60 papers in journals such as IEEE Sensors Journal and conferences like IEEE Globcom. Collaborative projects involve organizations like Panasonic, NEC, Orange Labs, and NTT Network. His work integrates machine learning with public health surveillance, energy management, and smart grid technologies.

Jean Christoph JungView profile

Professor

• Artificial Intelligence
• Knowledge Representation
• Logic in Computer Science
• +3 more

Prof. Jean Christoph Jung holds the Chair of Knowledge-Based Systems at TU Dortmund University since November 2022. He is affiliated with the Department of Computer Science within the Faculty of Computer Science. His academic journey includes a BSc in Computer Science (2006, TU Dresden), MSc in Computational Logic (2008, TU Dresden & Universidade Nova de Lisboa), and a PhD in Natural Sciences (2014, University of Bremen). Before his current position, he served as a research assistant at the University of Bremen (2009-2020), a postdoc at KU Leuven (2017/18), and an adjunct professor for Theoretical Computer Science at the University of Hildesheim (2020-2022). His research focuses on theoretical foundations of AI, logic-based knowledge representation (especially ontologies), and applications in computer science logic. Key contributions include work on ontology-mediated query answering, temporal logics, and PAC learning of logical concepts. He has co-authored numerous articles in top venues such as ICDT, DL, and AI conferences, addressing topics like query processing, logical separability, and formal verification. Though no specific grants or awards are mentioned, his extensive publication record highlights sustained contributions to the intersection of logic, databases, and AI. His work bridges theoretical advancements with practical applications in complex operational domains requiring robust knowledge representation systems.

• Database Systems
• Data Management
• Data Visualization
• +3 more

Eugene Wu is a Professor affiliated with Columbia University, specializing in database systems, data management, and visualization. His work bridges theoretical foundations with practical applications, focusing on systems that empower users through interactive analysis and human-in-the-loop processes. Key contributions include Smoke (lineage tracking), AlphaClean (automated data cleaning), and PI2 (interactive visualization generation). He has also explored privacy-preserving data systems (Saibot) and leveraging large language models (LLMs) for tasks like table profiling (Cocoon) and prompt development. Education: PhD from MIT in Computer Science Research spans database theory, visualization frameworks, and machine learning integration. Recent work emphasizes data quality (SPADE), privacy in distributed markets, and scalable training data debugging. He actively contributes to conferences like SIGMOD, CIDR, and VLDB, often chairing workshops on human-in-the-loop analytics. Articles focus on system design, theoretical advancements, and LLM applications in data management. Awards and recognition include sustained innovation in data systems and visualization. Advises on projects blending databases with emerging technologies like LLMs and decentralized data markets.

Francesco GuerraView profile

Professor

• Scalable Data Management
• Data Mining
• Big Data Analysis
• +5 more

Francesco Guerra is a Full Professor at the Department of Engineering 'Enzo Ferrari' at the University of Modena and Reggio Emilia. He teaches Software Engineering and Big Data Analysis. His research focuses on scalable data management, machine learning explainability, entity resolution, data mining, text analytics, semantic web, and keyword-based search on structured data. Academic Positions: Rector’s delegate for ICT (since Feb 2024) President of Computer Engineering Degree Councils (since Nov 2022) Curriculum Coordinator for Computer Engineering Doctorate (2021-2023) Visiting Professor at University of Rijeka (2019) Education: PhD in Information Engineering (2004) Master Degree in Information Engineering (2000) Classical Diploma (1992) from Liceo Classico 'L.A. Muratori' Research Interests: Develops explainable machine learning techniques for entity resolution and anomaly detection. Specializes in interpretable time series clustering (Time2Feat), BERT-based entity matching analysis, and pushing ML predictions into DBMS frameworks. Active in semantic keyword search and big data integration projects like KEYSTONE (COST Action 2013-2017) and Re-search Alps (2017-2019). Projects: KEYSTONE COST Action: Semantic keyword search on structured data Re-search Alps: Big data integration for Alpine research labs AutoML4Clust: Automated machine learning for clustering FAIRnessEval: Framework for algorithmic fairness evaluation Awards: No awards explicitly listed in the provided texts. However, his work has been funded through EU and national projects.

Ralf LämmelView profile

Professor

• Software Language Engineering
• Model-Driven Development
• Semantic Web
• +2 more

Ralf Lämmel is Professor and Head of the Software Languages group at the University of Koblenz. His research spans software language engineering, model-driven development, and semantic web technologies. He specializes in API analysis, data validation (SHACL constraints), and variability management for software systems. Recent work focuses on AI-assisted workflows for archaeology and trust analysis in large language models. Publications demonstrate growing interest in knowledge graph validation and semantic web applications. He has developed tools like the Virtual Platform for software variability and ProGS for property graph validation. Service includes program committee memberships for software engineering conferences and editorial roles. He leads research groups exploring API evolution and RDF validation techniques.

Michael GeneserethView profile

Professor

• Computational Logic
• Enterprise Management
• Computational Law
• +4 more

Michael Genesereth is a Professor of Computer Science at Stanford University and a professor by courtesy in the Stanford Law School. He serves as director of the Logic Group at Stanford and is the founder and research director of CodeX - the Stanford Center for Legal Informatics. Genesereth is renowned for his groundbreaking work on Computational Logic and its diverse applications in Enterprise Management, Computational Law, and General Game Playing. His academic journey includes an Sc.B. in Physics from M.I.T. and a Ph.D. in Applied Mathematics from Harvard University (1978). These foundational studies paved the way for his influential career at the intersection of logic, computer science, and law. Genesereth's research program spans from theoretical foundations of logic programming to practical implementations across multiple domains. His work on General Game Playing has established frameworks enabling AI systems to understand and play games based purely on logical descriptions of rules. In Computational Law, he pioneers approaches for representing legal rules in machine-processable formats to automate compliance checking and legal reasoning. His Logic For All initiative has successfully introduced logic education to high schools across the United States, with teachers reporting significant improvements in students' preparedness for college-level coursework. The publication pattern reveals a sustained research trajectory focused on logic foundations, with recent work expanding into practical applications in computational law, insurance portfolio management, and knowledge representation systems. His 2022-2025 publications demonstrate continued innovation in logic programming frameworks and their real-world implementations. Genesereth has founded multiple technology companies including Teknowledge, CommerceNet, Mergent Systems, and Symbium, translating theoretical work into practical solutions. His educational impact extends through widely adopted textbooks and his free massive open online course (MOOC) on Introduction to Logic, which has enrolled hundreds of thousands of students globally. His current initiatives include the International Logic Olympiad, launched in 2024, which engages high school students worldwide in logic problem-solving competitions. This effort builds on his observation that high school students consistently perform well in his university-level logic courses, demonstrating the readiness of secondary students for formal logic education.

• Semantic Web
• Knowledge Graphs
• Linked Data
• +3 more

Mohamed Ahmed Sherif is an academic affiliated with Paderborn University's Department of Computer Science and the University of Leipzig's Institute of Computer Science. His primary research focuses on semantic web technologies, knowledge graph integration, and machine learning applications in data integration. Key affiliations: Paderborn University, University of Leipzig Specialization: Link discovery, knowledge graph construction, semantic web standards His work emphasizes scalable methods for linking heterogeneous data sources, explainable AI techniques for knowledge integration, and geospatial semantic technologies. Recent contributions include the ANTS system for entity summarization in knowledge graphs and the NELLIE framework for continuous linked data integration. Notable projects include LIMES - a widely-used link discovery framework - and contributions to the HOBBIT benchmarking platform. His research has been applied in disaster management (I-AID system), Quran semantification, and global health data integration.

Milosh JovanovikjView profile

Associate Professor

• Knowledge Graphs
• Data Engineering
• Semantic Web
• +8 more

Dr. Milosh Jovanovikj holds the role of Associate Professor at the Faculty of Computer Science and Engineering in Skopje, North Macedonia, and concurrently serves as a PostDoc Researcher at TU Wien in Vienna, Austria. He is also a Senior R&D Knowledge Graphs Engineer at OpenLink Software in London. His primary research focuses on Knowledge Graphs (KGs), including their lifecycle processes such as modeling, enrichment, and analytics-driven AI applications. He has contributed to over 10 international and 25 national research projects, authored 60+ publications, and co-authored 3 books. His expertise spans Data Engineering, Semantic Web technologies, Linked Data, and Applied AI. Significant contributions include developing frameworks like RDFGraphGen for RDF graph generation and PharmKE for pharmaceutical text analysis. He has led initiatives in geospatial semantic web standards (GeoSPARQL) and healthcare informatics, including predictive analytics for nephrology data. Education: PhD in Computer Science and Engineering His work bridges academia and industry, with projects like the 3DFed federation engine and Semantic Sky (a Gmail plugin). He has extensive experience in ontology development (e.g., SEOntology, VEO for CO2 emissions) and open data initiatives, including LinkedDrugs for global drug data consolidation. Active in dissemination, his articles span knowledge graph applications in music recommendation, finance sentiment analysis, and drug-disease relation discovery. He has collaborated on benchmarks like the GeoSPARQL Compliance Benchmark and Mighty Storage Challenge (MOCHA). Grants/Projects: HOBBIT, SAGE, 3DFed, LinkedDrugs He leads teams in advancing semantic web integration, cloud service platforms (Semantic Sky), and educational materials like Web Programming Basics . His labs and teams focus on AI-driven solutions for healthcare, geospatial analytics, and enterprise systems.

Guy De TréView profile

Associate Professor

• Computational Intelligence
• Data Quality
• Decision Support Systems
• +7 more

Guy De Tré is an Associate Professor at the Department of Telecommunications and Information Processing within Ghent University's Faculty of Engineering and Architecture. He leads the Database, Document and Content Management (DDCM) research group and focuses on computational intelligence in information systems, with expertise in bi-polarity handling, uncertainty modeling, and multi-valued logic systems. Primary Affiliation: Ghent University Research Focus: Data quality, fuzzy querying, spatio-temporal modeling Key Contributions: Foundational work in possibilistic databases and explainable AI His research combines theoretical and applied approaches to information management systems. Theoretical work includes: Bipolarity and uncertainty handling in databases Multi-valued logic frameworks Interval B-tree indexing for possibilistic data Applied research spans: NoSQL database optimization Decision support systems Contextualized machine learning 3D/4D modeling for geological resources Recent publications show increasing focus on explainable AI, with multiple works on contextualized support vector machine classification and orthographic similarity measures for graph-based data representations. His work bridges database theory with practical applications in data quality assessment, medical informatics, and cultural heritage projects like the Byzantine Book Epigrams database. Research Group: Leads the DDCM group at Ghent University, specializing in: Database management innovation Content modeling techniques Fuzzy logic implementations Temporal data indexing Intelligent information systems